Abstract Given the multifactorial pathophysiological cascades involved in traumatic brain injury (TBI), it is difficult if not impossible to have a thorough view of the molecular mechanisms underlying the complexity of this pathology based on limited information derived from conventional approaches that examine isolated molecular events. This complexity becomes a larger limiting factor for the design of strategies to diagnose and predict the outcome of mild TBI (mTBI) which has a less defined symptomatology. Genomic profiling is emerging as a powerful tool to retrieve fundamental information about gene regulatory mechanisms that govern the mTBI pathology and its diversion towards other neurological disorders. However, genomic studies of mTBI have been primarily based on the use of whole brain regions comprised of heterogeneous cell types that mask information from the most vulnerable cell types which are crucial drivers of the pathogenesis. The unique aspect of our approach is to determine the genomic signatures of mTBI at single-cell resolution as cells are the basic units of biological structure and function. We will use state-of-the-art Drop-seq technology that empowers us to capture the transcriptome of thousands of individual brain cells in parallel to accurately define cell types based on aggregate genomic features and, more importantly, to identify cell-type specific gene markers of mTBI, which are generally hidden to the eyes of conventional approaches. We propose experiments to classify all the cell types in the hippocampus (one of the main action sites of TBI) in an unbiased manner and to assess the vulnerability of each cell type to mTBI using single-cell transcriptome profiles (Aim 1). In addition, we will define cell-type specific signatures of genes that could characterize main events involved in our rodent model of mTBI with varying severity at different time points post-TBI (Aim 2). We expect to retrieve novel cell types defined by the effects of mTBI, and their associated deterministic gene markers in the hippocampus. In doing so, we expect to unravel the fundamental, cell specific gene signatures that can be used as biomarkers of mTBI in a data-driven, unbiased manner. Our findings will derive clues to the underlying molecular events and pathways driving the cellular and functional remodeling. This proposal offers the unique opportunity to synergize efforts by combining the expertise of Dr. Fernando Gomez-Pinilla in TBI and the expertise of Dr. Xia Yang in genomics, bioinformatics, and systems biology of complex disorders. The overall goal of the proposal is to elaborate on an innovative research strategy that can provide a comprehensive understanding of the mTBI pathology at single cell resolution, which can be used to empower patient diagnosis, and to design a new line of strategies to redirect the courses of TBI and overcome subsequent neurological disorders.